BMC Cancer · 2018 · 69 citations · 21 references
MedicineBiostatisticsOncologyBreast OncologyCancer EpidemiologyMolecular OncologyBreast Cancer Risk AssessmentCancer RiskMalignant NeoplasmsBreast Cancer Molecular SubtypesBreast Cancer Risk StratificationBreast Tumor ClassificationCox RegressionImmunohistochemical BiomarkersMenopausal StatusPostmenopausal Hormone TherapyProspective Cohort Data
Earlier epidemiological studies indicate that associations between obesity and breast cancer risk may not only depend on menopausal status and use of exogenous hormones, but might also differ by tumor subtype. Here, we evaluated whether obesity is differentially associated with the risk of breast tumor subtypes, as defined by 6 immunohistochemical markers (ER, PR, HER2, Ki67, Bcl-2 and p53, separately and combined), in the prospective EPIC-Germany Study ( n = 27,012). Formalin-fixed and paraffin-embedded (FFPE) tumor tissues of 657 incident breast cancer cases were used for histopathological analyses. Associations between BMI and breast cancer risk across subtypes were evaluated by multivariable Cox regression models stratified by menopausal status and hormone therapy (HT) use. Among postmenopausal non-users of HT, higher BMI was significantly associated with an increased risk of less aggressive, i.e. ER+, PR+, HER2-, Ki67 low , Bcl-2+ and p53- tumors (HR per 5 kg/m 2 : 1.44 [1.10, 1.90], p = 0.009), but not with risk of more aggressive tumor subtypes. Among postmenopausal users of HT, BMI was significantly inversely associated with less aggressive tumors (HR per 5 kg/m 2 : 0.68 [0.50, 0.94], p = 0.018). Finally, among pre- and perimenopausal women, Cox regression models did not reveal significant linear associations between BMI and risk of any tumor subtype, although analyses by BMI tertiles showed a significantly lower risk of less aggressive tumors for women in the highest tertile (HR: 0.55 [0.33, 0.93]). Overall, our results suggest that obesity is related to risk of breast tumors with lower aggressiveness, a finding that requires replication in larger-scale analyses of pooled prospective data.
21
R: A Language and Environment for Statistical Computing
R Core Team · 2000 · 353K citations · Full text
Natural Sciences, Computer Science, Statistical Computing +10
Antonio C. Wolff, M. Elizabeth Hammond, David G. Hicks et al. · Journal of Clinical Oncology · 2013 · 4.1K citations · Full text
PUMA, a Novel Proapoptotic Gene, Is Induced by p53
Katsunori Nakano, Karen H. Vousden · Molecular Cell · 2001 · 2.3K citations · Full text
Jennet Harvey, Gary M. Clark, C. Kent Osborne et al. · Journal of Clinical Oncology · 1999 · 2.1K citations
Medicine, Endocrinology, Oncology +17
Alan S. Coates, Eric P. Winer, Aron Goldhirsch et al. · Annals of Oncology · 2015 · 1.8K citations · Full text